DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This action is pursuant to claims filed on 01/27/2023. Claims 1- 20 are pending. A first action on the merits of claims 1- 20 is as follows.
Priority
Priority Acknowledgement is made of applicant’s claim of domestic benefit to provisional application No. 63/267,278 filed on 01/28/2022.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 05/01/2023, 06/20/2023, and 01/26/2024 have been considered by the Examiner.
Claim Objections
Claims 4, are objected to because of the following informalities:
Claim 4, line 2: “an electric-analogy model” should read “the electric-analog model”.
Claim 16, lines 1-2: “comparing modeled admittance over a frequency” should read “comparing a modeled admittance over a frequency”.
Appropriate correction is required.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
Claim limitations being interpreted under 35 U.S.C. 112(f), and the identified structure, material, or act disclosed in the specification that supports the recited functions, are as follows:
“a diagnostic tool for non-invasively acquiring an acoustic measurement from an ear canal” of claim 11.
“a device for obtaining an acoustic measurement from an ear canal” of claim 17.
Corresponding Structure: see [0150], “…algorithms and machine learning networks, could be implemented with devices, such as WAI devices that are used in clinical settings…WAI tool could be used to non-invasively acquire the data from a patient in the clinic or other setting, and the tool or an associated network (e.g., a computer, server, processor, or the like) could quickly receive the acoustic data and provide the output information…”. See also [0129], “…WAI data acquisition is generally considered non-invasive (e.g., a probe tip is quickly inserted into an ear canal)…”.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 4, 6, and all claims dependent thereon, are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 4 recites “…wherein the step of modeling the acoustic measurement with an electric-analogy model comprises utilizing a model comprising a nonuniform transmission line…” in lines 1-2. The electric-analog model appears to include a non-uniform transmission line of ear canal components, and further appears to represent acoustic responses of a human ear canal (applicant’s [0089]). However, the electric-analog model does not appear to “comprise utilizing a model comprising a non-uniform transmission line”. This renders the scope of the claim unclear, as there is ambiguity regarding what model applicant intends to use to manipulate received data.
Claim 6 recites “…wherein the network of the model comprises three parallel branches…” in lines 1-2. It is unclear whether applicant is referring to the electric-analog model, or the model comprising a non-uniform transmission line, both of which are recited in claim 4 from which claim 6 depends. This renders the scope of the claim unclear, as there is ambiguity regarding which model applicant intends to apply to manipulate data.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. A streamlined analysis of claim 1 follows.
Regarding claim 1, the claim recites a method of estimating an ear condition. Thus, the claim is directed to a method, which is one of the statutory categories of invention.
Having determined that the claims are drawn to one of the statutory categories, the claim is then analyzed to determine whether it is directed to any judicial exception. The following limitations set forth a judicial exception:
[A1]: “… modeling the acoustic measurement with an electric-analog model…”.
[B1]: “… transforming the model output to a measured admittance...”.
[C1]: “… training a machine learning network, wherein the training comprises...fitting the
parameters of the model such that the transformed model output correlates to the measured ear condition data...”;
[D1]: “...and identifying one or more classifiers of the transformed model output that provides an estimate of the ear condition”.
These limitations describe a mathematical calculation/relationship. Furthermore, the limitations also describe a mental process as the skilled artisan is capable of performing the recited limitations and making a mental assessment thereafter. Examiner also notes that nothing from the claims suggest that the limitations cannot be practically performed by a human, or using simple pen/paper.
For example, modeling an acoustic measurement can be done with math such as transfer functions (applicants [0082]), transforming a model output to a measured admittance can be done with math such as determining the reciprocal of impedance (applicants [0097]), fitting model parameters can be done with math such as comparing differences between measured and modeled values (applicants [0109]), or by looking at the graph of modeled and measured absorbance and circling the region of interest that best fits measured data (i.e., a mental process), and one can identify classifier(s) estimating an ear condition using math such as regression analysis (applicants [0132]).
Next, the claim as a whole is analyzed to determine whether any element, or combination of elements, integrates the identified judicial exception into a practical application.
For this part of the 101 analysis, the following additional limitations are considered:
[A2]: “… obtaining an acoustic measurement from an ear canal…”.
[B2]: “… modeling the acoustic measurement with an electric-analog model to obtain a model output...”.
[C2]: “… wherein the training comprises: acquiring measured ear condition data...”.
These additional limitations do not integrate the judicial exception into a practical application for several reasons. Rather, the additional limitations are each recited at a high level of generality such that it amounts to insignificant pre-solution and post-solution activity, e.g., mere data gathering steps necessary to perform the identified judicial exception (see MPEP 2106.05(g) examples of activities that the courts have found to be insignificant extra-solution activity includes mere data gathering and outputting).
The additional limitations also do not add significantly more to the identified judicial exception.
Particularly, simply reciting the additional limitations of [A2]-[C2] do not amount to significantly more than the judicial exception because acquiring ear condition data in the manner recited is well-known, routine, and conventional (see for example US 2019/0046089 A1 to Pislak et al. (“Pislak”), which discloses sample sound signals are well known for routinely representing measured ear condition data see [0027], “...it has been established that sample sound signals (emitted in the ear canal by way of said probe element or otherwise) are representative of an actual situation in the ear canal ...”).
Furthermore, it is well established by the courts that the mere physical or tangible nature of additional elements such as the obtaining and measuring steps do not automatically confer eligibility on a claim directed to an abstract idea (see, e.g., Alice Corp. v. CLS Bank Int'l, 134 S.Ct. 2347, 2358-59 (2014)).
Independent claims 11 and 17 recite mirrored limitations and are also not patent eligible for substantially similar reasons.
Dependent claims 2-10, 12-16, and 18-20 also fail to add something more to the abstract independent claims as they merely further limit the abstract idea, recite limitations that do not integrate the claims into a practical application for substantially similar reasons as set forth above, and/or do not recite significantly more than the identified abstract idea for substantially similar reasons as set forth above.
Examiner further notes that there does not appear to be language in the specification showing that the system is made more efficient or powerful by the operations set forth by the claims. It only appears to offer a better model for determining an ear condition, bringing the claims more in line with those that have been found ineligible in Parker v. Flook, 437 U.S. 584, 588-89, 198 USPQ2d 193, 195 (1978) and Digitech Image Techs., LLC v. Electronics for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014).
Therefore, claims 1-20 are not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-3 , 9-13, 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over US 2021/0321911 A1 to Magnussen et al. (“Magnussen”) in view of US 2022/0248148 to Verhulst et al. (“Verhulst”).
Regarding independent claims 1, 11 and 17, Magnussen teaches a system and method of estimating an ear condition (see [0019], “...wideband acoustic immittance measurement apparatus for determination of wideband acoustic immittance F(f) in an ear of a human is provided for characterization of the middle ear of the human....”) comprising:
A device for obtaining an acoustic measurement from an ear canal; (see Fig. 2 and [0150], “... a wideband acoustic immittance measurement apparatus 10 with the ear probe 12 positioned with its acoustic output port at or inside an ear canal 100 of an ear 110 of a human...”, apparatus acquires an acoustic measurement from an ear canal), operatively connected to a computer readable medium (see [0071]-[0072], “... wideband acoustic immittance measurement apparatus...comprises... a processor...”),
modeling the acoustic measurement with an electric-analog model to obtain a model output (see Fig. 1 and [0041]-[0043], “...equivalent circuit for an immittance measurement performed with an ear probe... see also [0050], “Measurements of sound pressure P at two different acoustic loads with known acoustic impedances ZA and ZB allow the calculation of the two equivalent circuit parameters of the sound source P0 and Z0”, equivalent circuit (i.e., electric-analog model) models measurement of sound pressure P (i.e., acoustic measurement) to obtain a model output (i.e., equivalent circuit parameters));
transforming the model output to a measured admittance (see [0054]-[0055], “... based on the determined acoustic impedance Z, other acoustic immittances may be derived, such as...The complex acoustic admittance Y”);
Magnussen further discloses polynomial fitting of middle ear resonance parameters (see [0243], “... middle ear resonances of the determined wideband acoustic immittance F (f, p) may be detected using simple peak detection methods and/or polynomial fits...”), and identifying a middle ear resonance based on a comparison of a determined wideband acoustic immittance to a resonance frequency (see [0022], “...middle ear resonance may be identified based on a comparison of characteristics of the determined wideband acoustic immittance F(f) with corresponding characteristics at the resonance frequency...”).
However, Magnussen fails to disclose ‘... training a machine learning network, wherein the training comprises: acquiring measured ear condition data; fitting the parameters of the model such that the transformed model output correlates to the measured ear condition data; and identifying one or more classifiers of the transformed model output that provides an estimate of the ear condition.”
Verhulst teaches a system and method for emulating human auditory processing (see abstract “...method and hearing device (100) for emulating cochlear processing of auditory stimuli...”) including a model output (see [0169], “... element-wise summed or element-wise summed and nonlinearly transformed...”) and further including training a machine learning network (see Fig. 14 and [0088], “... extract, approximate, train and evaluate the outputs of the different stages of the auditory periphery model...”,) wherein the training comprises:
acquiring measured ear condition data; fitting the parameters of the model such that the transformed model output correlates to the measured ear condition data (see [0134], “... biophysically accurate transmission line model capturing and modelling the hearing impairment, e.g. based on known effects or measured individual audiograms, otoacoustic emissions (OAEs), or auditory evoked potentials (AEPs)...hearing-damage parameters derived from measured audiograms or auditory evoked potentials can easily be used to train an individualized neural network model...” , acquiring measured audiogram data with known effects (i.e., measured ear condition data) and deriving hearing-damaged parameters to correlate with ear condition data (i.e., fitting parameters of the model)); and identifying one or more classifiers of the transformed model output that provides an estimate of the ear condition (see [0145], “...train the hearing-aid model to compensate for a single aspect of hearing damage (e.g. outer-hair-cell damage or synaptopathy)...”).
Magnussen discloses a system estimating an ear condition, including a device for taking an acoustic measurement from an ear canal coupled to a computer readable medium, an analog circuit model modeling ear mechanics, and transforming the model output to an admittance, but fails to disclose training a machine learning network. Verhulst teaches training a machine learning network emulating human auditory processing.
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to modify Magnussen to train a machine learning network as taught by Verhulst, for the purpose of improving computational expense, as evidence by Verhulst (see [0004]). Furthermore, one of ordinary skill in the art would have had predictable success combining and Magnussen and Verhulst since both teachings relate to the same narrow field of endeavor, i.e., auditory modeling of human hearing.
Regarding claims 2 and 12: The Magnussen/Verhulst combination teaches the system and method of claims 1 and 11, as discussed above. The Magnussen/Verhulst combination further teaches wherein the acoustic measurement comprises an impedance-based measurement (see Magnussen [0050], “…Measurements of sound pressure P at two different acoustic loads with known acoustic impedances…”, impedance based measurement).
Regarding claims 3 and 13: The Magnussen/Verhulst combination teaches the system and method of claims 1 and 11, as discussed above. The Magnussen/Verhulst combination further teaches wherein the impedance based measurement comprises a wideband acoustic immittance (see Magnussen [0019], “...wideband acoustic immittance measurement apparatus for determination of wideband acoustic immittance F(f) in an ear of a human is provided for characterization of the middle ear of the human....”).
Regarding claims 9 and 10: The Magnussen/Verhulst combination teaches the system of method of claim 1, as discussed above. The Magnussen/Verhulst combination further teaches implementing the trained machine learning network (of the Magnussen/Verhulst combination, as described above) into a system (see Magnussen [0002], “…a system and method for wideband acoustic immittance measurement…”) including a diagnostic tool and associated processor wherein the tool acquires the acoustic measurement, (see Magnussen Fig. 2 and [0150], “... a wideband acoustic immittance measurement apparatus 10 with the ear probe 12 positioned with its acoustic output port at or inside an ear canal 100 of an ear 110 of a human...”, see also [0155], “…processor 28 is also connected to the output of the microphone 22 for reception of the input audio signal 26 generated by the microphone 22 in response to sound received at the input port of the ear probe 12…”, measurement apparatus connected to a processor (i.e., processor associated with measurement apparatus of the Magnussen/Verhulst combination, as described above) acquires an acoustic measurement from an ear canal) and the processor estimates the ear condition (see Verhulst [0158], “…processing device 102…may comprise one or more dedicated processing elements for executing a computer program code such that…processing device 102 effectively performs the data processing steps of a neural network…”), wherein the diagnostic tool is connected to the processor in a wired or wireless manner (see Verhulst [0161], “…sound sensing element(s), e.g.…the sampling means 103, the processing device 102, and the acoustic transducer 105 may be interconnected by wire connections or by a wireless (network) connection…”).
Regarding claim 16: The Magnussen/Verhulst combination teaches the system of claim 11, as discussed above. However, the Magnussen/Verhulst combination fails to explicitly disclose wherein the training method (of the Magnussen/Verhulst combination) further comprises comparing modeled admittance over a frequency.
Magnussen further discloses determining acoustic immittance as a function of frequency based on audio signal input and output (see [0075], “…determining wideband acoustic immittance F(f) as a function of frequency f based on the output audio signal and the input audio signal”) and further discloses comparing determined acoustic admittances as a function of frequency (see [0216], “…determining a baseline compensated acoustic admittance…between a determined acoustic admittance…as a function of frequency f at a first static pressure…and a determined acoustic admittance…as a function of frequency f at a second static pressure…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the training method of the Magnussen/Verhulst combination, to compare modeled admittance over a frequency, for the purpose of accounting for the effect of ear mechanics on measured parameters, as evidence by Magnussen (see [0010]).
Claims 4-8, 14, 15, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Magnussen in view of Verhulst, and further in view of a research article entitled “The influence of otitis media with effusion on middle-ear impedance estimated from wideband acoustic immittance measurements” by Merchant et al. (Cited in 05/01/2023 IDS).
Regarding claim 4: The Magnussen/Verhulst combination teaches the method of claim 1, as discussed above. The Magnussen/Verhulst combination further teaches modeling immittance measurements of an ear canal with an equivalent circuit containing three components (see Magnussen Fig. 1 and [0040]-[0042] and [0050], “…a Thévenin equivalent circuit for an immittance measurement performed with an ear probe… modelled by an ideal sound pressure generator…in series with a source impedance…which is connected in series with the acoustic load Z…”, three components (i.e., zero source impedance pressure generator, zero source impedance, and acoustic load) used to model ear probe acoustic measurements).
However, the Magnussen/Verhulst combination fails to explicitly disclose wherein the step of modeling the acoustic measurement with an electric-analogy model comprises utilizing a model comprising a nonuniform transmission line terminated by a network of at least three sets of components each having three inputs, which correspond to human middle ear mechanics.
Merchant teaches a method for estimating middle ear impedance from WAI measurements using an electric-analog model (see pg. 970, col. 1 par. 2, “…estimation procedure…fitting measurements of the ear-canal impedance taken from WAI measurements to an electrical-analog model that represents ear-canal acoustics and middle-ear mechanics …”), the model including a non-uniform transmission line terminated by a three component network (see Fig. 2 and pg. 971, col. 1 par. 1, “…electrical-analog model of ear-canal acoustics and middle-ear mechanics…comprises a nonuniform transmission line that is terminated by a network of stiffness (K), damping (R), and mass (M) components”, stiffness, damping, and mass components (i.e., three component network)), each component having three inputs, corresponding to human middle ear mechanics (see Fig. 2 and pg. 971, col. 1 par. 1, “…middle-ear network contains three branches that together represent the mechanics of the TM coupled to the ossicles…input impedance is calculated as the parallel impedance of these three branches…”, each stiffness, damping, and mass component has three inputs (i.e., K1-K3, R1-R3, and M1-M3) representative of ear mechanics).
Although the Magnussen/Verhulst combination teaches modeling acoustic measurements with an electric-analog model to obtain a model output (see Magnussen Fig. 1 and [0041]-[0043] and [0050]), the Magnussen/Verhulst combination fails to disclose a model as recited in claim 4 above. Merchant teaches modeling acoustic measurements with an electric-analog model having a nonuniform transmission line terminated by a network of stiffness, damping, and mass components, each with three inputs, corresponding to middle ear mechanics (see Fig. 2 and pg. 971 col. 1).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Magnussen/Verhulst combination (to include a non-uniform transmission line terminated by three components, each with three inputs, representing ear mechanics), for the purpose of accounting for changes in acoustic impedance resulting from alterations in middle ear mechanics, as evidence by Merchant (see pg. 969). Furthermore, one of ordinary skill in the art would have had predictable success combining Magnussen, Verhulst, and Merchant since their teachings relate to the same narrow field of endeavor, i.e., utilizing acoustic measurements to characterize various types of bio-information.
Regarding claim 5: The Magnussen/Verhulst/Merchant combination teaches the method of claim 4/1, as discussed above. The Magnussen/Verhulst/Merchant combination further teaches wherein the step of modeling the acoustic measurement further comprises a transmission line representing the ear canal terminated by the network (see Merchant Fig. 2 and pg. 971 col. 1 par. 1, “…transmission line represents the ear canal, whereas the terminating circuit represents the middle ear…”).
Regarding claim 6: The Magnussen/Verhulst combination teaches the method of claims 5/4/1, as discussed above. The Magnussen/Verhulst combination further teaches wherein the network of the model comprises three parallel branches, with each branch comprising a stiffness, damping, and mass component, wherein the network represents mechanics of a tympanic membrane coupled to ossicles of an ear (see Merchant Fig. 2 and pg. 971, col. 1 par. 1, “…electrical-analog model of ear-canal acoustics and middle-ear mechanics…comprises a nonuniform transmission line that is terminated by a network of stiffness (K), damping (R), and mass (M) components…“…middle-ear network contains three branches that together represent the mechanics of the TM coupled to the ossicles…”).
Regarding claims 7 and 14: The Magnussen/Verhulst combination teaches the system and method of claims 1 and 11, as discussed above. Magnussen further teaches determining instability of measured ear cavity volume (see [0246], “… indicate measurement status, such as…instability of the measured ear cavity volume…” ). Additionally, Verhulst further teaches estimating individualized hearing loss profiles of individuals (see [0144], “…exact auditory profile of hearing loss is estimated for an individual…can accurately compensate for the specific hearing impairment…hearing impairment profile can include outer-hair-cell damage, inner-hair-cell damage, cochlear synaptopathy, or even combinations of hearing loss in all different stages of the auditory periphery…”).
However, the Magnussen/Verhulst combination fails to explicitly disclose wherein the ear condition comprises an effusion volume in an ear.
Merchant teaches a method for estimating middle ear impedance from WAI measurements in an ear canal (see pg. 969, col. 1 par. 1, “…ear-canal acoustic measures, which include admittance, impedance, reflectance, and absorbance, are collectively known as wideband acoustic immittance (WAI)… measurements are made in the ear canal in response to wideband stimuli…”), further teaches a relationship between WAI measurements and conductive hearing loss (see pg. 969, col. 1 par. 1, “…WAI have been demonstrated to have clinical utility in the assessment of middle-ear status, particularly in differentiating origins of conductive hearing loss…”) ,and using WAI measurements to estimate effusion volume in an ear (see pg. 970 col. 1 par. 2, “…utility of WAI in predicting OME effusion volume…”).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Magnussen/Verhulst combination (to estimate an effusion volume in an ear), for the purpose of assessing and differentiating origins of conductive hearing loss, as evidence by Merchant (see pg. 969).
Regarding claims 8, 15 and 18: The Magnussen/Verhulst combination teaches the system and method of claims 7/1, 14/11, and 17, as discussed above.
However, the Magnussen/Verhulst combination fails to explicitly disclose wherein the classifiers identified by the machine learning network comprises full effusion, partial effusion, clear effusion, or normal ears.
Merchant teaches separating results of WAI testing into four groups based on levels of ear effusion volume (see pg. 970, col. 2 par. 1, “…separated into three groups…ears that were completely full of effusion…ears that were partially full of effusion…ears…that were clear of effusion…group of age-matched normal hearing control ears…were also included for comparison…”, classifying levels of effusion into three groups (i.e., completely full, partially full, clear) and a fourth group as a ground truth comparison (i.e., normal)).
Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Magnussen/Verhulst/Merchant combination (to identify effusion volume classifiers as full, partial, clear, or normal), for the purpose of improving the distinction between healthy ears and ears with effusion, as evidence by Merchant (see pg. 969, abstract).
Regarding claim 19: The Magnussen/Verhulst teaches the system of claim 16/11, as discussed above. The Magnussen/Verhulst combination further teaches modeling immittance measurements of an ear canal with an equivalent circuit containing three components (see Magnussen Fig. 1 and [0040]-[0042] and [0050], “…a Thévenin equivalent circuit for an immittance measurement performed with an ear probe… modelled by an ideal sound pressure generator…in series with a source impedance…which is connected in series with the acoustic load Z…”, three components (i.e., zero source impedance pressure generator, zero source impedance, and acoustic load) used to model ear probe acoustic measurements).
However, the Magnussen/Verhulst combination fails to explicitly disclose wherein the electric-analog model comprises a transmission line representing the ear canal terminated by the network.
Merchant teaches a method for estimating middle ear impedance from WAI measurements using an electric-analog model (see pg. 970, col. 1 par. 2, “…estimation procedure…fitting measurements of the ear-canal impedance taken from WAI measurements to an electrical-analog model that represents ear-canal acoustics and middle-ear mechanics …”), the model including a transmission line representing the ear canal terminated by the network (see Merchant Fig. 2 and pg. 971 col. 1 par. 1, “…transmission line represents the ear canal, whereas the terminating circuit represents the middle ear…”).
Although the Magnussen/Verhulst combination fails to explicitly disclose a terminal representing the ear canal, Magnussen further teaches redundancy of the ear canal in admittance characterization of the middle ear (see Magnussen [0111], “…ear canal is however redundant to the characteristics of the middle and inner ear and therefore it may be desirable to eliminate or reduce the contribution of the ear canal from the determined wideband acoustic immittance F(f), e.g. acoustic admittance Y(f)…”). Therefore, it would have been prima facie obvious to one having ordinary skill in the art at the time the invention was filed to further modify the Magnussen/Verhulst combination (to include a transmission line representing the ear canal), for the purpose of reducing error potential introduced when modeling ear canal geometry, as evidence by Merchant (see pg. 977, col. 1-2, par. 3).
Regarding claim 20: The Magnussen/Verhulst/Merchant combination teaches the system of claim 18/17, as discussed above. The Magnussen/Verhulst/Merchant combination further teaches wherein the model comprises a nonuniform transmission line terminated by a network of at least three sets of components (see Fig. 2 and pg. 971, col. 1 par. 1, “…electrical-analog model of ear-canal acoustics and middle-ear mechanics…comprises a nonuniform transmission line that is terminated by a network of stiffness (K), damping (R), and mass (M) components”, stiffness, damping, and mass components (i.e., three component network)), each having three inputs, which correspond to human middle ear mechanics (see Fig. 2 and pg. 971, col. 1 par. 1, “…middle-ear network contains three branches that together represent the mechanics of the TM coupled to the ossicles…input impedance is calculated as the parallel impedance of these three branches…”, each stiffness, damping, and mass component has three inputs (i.e., K1-K3, R1-R3, and M1-M3) representative of ear mechanics).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALYSSA P NOVAK whose telephone number is (703)756-1947. The examiner can normally be reached M-F: 8-5.
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/ALYSSA PAIGE NOVAK/Examiner, Art Unit 3791
/ERIC J MESSERSMITH/Primary Examiner, Art Unit 3791